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At least 19 recordsLinked to original sources
USGS2011

Predicting community responses to perturbations in the face of imperfect knowledge and network complexity

How best to predict the effects of perturbations to ecological communities has been a long-standing goal for both applied and basic ecology. This quest has recently been revived by new empirical data, new analysis methods, and increased computing speed, with the promise that ecologically important insights may be obtainable from a limited knowledge of community interactions. We use empirically based and simulated networks of varying size and connectance to assess two limitations to predicting perturbation responses in multispecies communities: (1) the inaccuracy by which species interaction strengths are empirically quantified and (2) the indeterminacy of species responses due to indirect effects associated with network size and structure. We find that even modest levels of species richness and connectance (∼25 pairwise interactions) impose high requirements for interaction strength estimates because system indeterminacy rapidly overwhelms predictive insights. Nevertheless, even poorly estimated interaction strengths provide greater average predictive certainty than an approach that uses only the sign of each interaction. Our simulations provide guidance in dealing with the trade-offs involved in maximizing the utility of network approaches for predicting dynamics in multispecies communities.

Ecology↗
USGS2017

Foundations of translational ecology

Ecologists who specialize in translational ecology (TE) seek to link ecological knowledge to decision making by integrating ecological science with the full complement of social dimensions that underlie today's complex environmental issues. TE is motivated by a search for outcomes that directly serve the needs of natural resource managers and decision makers. This objective distinguishes it from both basic and applied ecological research and, as a practice, it deliberately extends research beyond theory or opportunistic applications. TE is uniquely positioned to address complex issues through interdisciplinary team approaches and integrated scientist–practitioner partnerships. The creativity and context‐specific knowledge of resource managers, practitioners, and decision makers inform and enrich the scientific process and help shape use‐driven, actionable science. Moreover, addressing research questions that arise from on‐the‐ground management issues – as opposed to the top‐down or expert‐oriented perspectives of traditional science – can foster the high levels of trust and commitment that are critical for long‐term, sustained engagement between partners.

Frontiers in Ecology and the Environment↗
USGS2018

A method to detect discontinuities in census data

The distribution of pattern across scales has predictive power in the analysis of complex systems. Discontinuity approaches remain a fruitful avenue of research in the quest for quantitative measures of resilience because discontinuity analysis provides an objective means of identifying scales in complex systems and facilitates delineation of hierarchical patterns in processes, structure, and resources. However, current discontinuity methods have been considered too subjective, too complicated and opaque, or have become computationally obsolete; given the ubiquity of discontinuities in ecological and other complex systems, a simple and transparent method for detection is needed. In this study, we present a method to detect discontinuities in census data based on resampling of a neutral model and provide the R code used to run the analyses. This method has the potential for advancing basic and applied ecological research.

Ecology and Evolution↗
USGS2016

Estimating indices of range shifts in birds using dynamic models when detection is imperfect

There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near-term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology.

Global Change Biology↗
USGS2020

A graphical causal model for resolving species identity effects and biodiversity–ecosystem function correlations

Identifying and clearly communicating the drivers of ecosystem function is a crucially important goal for both basic and applied ecology. This has proven difficult because the putative causes (e.g., environment, species identity, biodiversity, and functional traits) are numerous and correlated. The problem is exacerbated by a lack of a formal framework for unambiguously relating theoretical language to precise, quantitative expressions of that language. Using a formal framework for the graphical expression of complex causal hypotheses, we developed a causal diagram of the concepts required to comprehensively test whether hypothesized sets of functional traits mediate the relationship between community structure and ecosystem function. We then used causal analysis, simulations, and field data to develop and test analytical strategies for understanding how community structure influences ecosystem functions via functional traits. Formal causal analysis showed that biodiversity–ecosystem function correlations are non‐causal associations. Using simulations, we showed how biodiversity correlations and species identity effects can arise from misspecification or incomplete mediation by functional trait composites. We also found that different types of model misspecification result in different patterns of residuals, which may be used to diagnose gaps in functional trait hypotheses. Treating the model misspecifications eliminated associations between species identity or biodiversity and ecosystem function. Finally, we provide an example of the analysis of field data to demonstrate how to use these insights to conduct a research program that has the goal of understanding the mechanistic trait relationships that link community structure to ecosystem function.

Ecology↗
USGS2013

Human-caused mortality influences spatial population dynamics: pumas in landscapes with varying mortality risks

An understanding of how stressors affect dispersal attributes and the contribution of local populations to multi-population dynamics are of immediate value to basic and applied ecology. Puma (Puma concolor) populations are expected to be influenced by inter-population movements and susceptible to human-induced source–sink dynamics. Using long-term datasets we quantified the contribution of two puma populations to operationally define them as sources or sinks. The puma population in the Northern Greater Yellowstone Ecosystem (NGYE) was largely insulated from human-induced mortality by Yellowstone National Park. Pumas in the western Montana Garnet Mountain system were exposed to greater human-induced mortality, which changed over the study due to the closure of a 915 km 2 area to hunting. The NGYE’s population growth depended on inter-population movements, as did its ability to act as a source to the larger region. The heavily hunted Garnet area was a sink with a declining population until the hunting closure, after which it became a source with positive intrinsic growth and a 16× increase in emigration. We also examined the spatial and temporal characteristics of individual dispersal attributes (emigration, dispersal distance, establishment success) of subadult pumas (N = 126). Human-caused mortality was found to negatively impact all three dispersal components. Our results demonstrate the influence of human-induced mortality on not only within population vital rates, but also inter-population vital rates, affecting the magnitude and mechanisms of local population’s contribution to the larger metapopulation.

Biological Conservation↗
USGS2015

Performance metrics and variance partitioning reveal sources of uncertainty in species distribution models

Species distribution models (SDMs) are widely used in basic and applied ecology, making it important to understand sources and magnitudes of uncertainty in SDM performance and predictions. We analyzed SDM performance and partitioned variance among prediction maps for 15 rare vertebrate species in the southeastern USA using all possible combinations of seven potential sources of uncertainty in SDMs: algorithms, climate datasets, model domain, species presences, variable collinearity, CO 2 emissions scenarios, and general circulation models. The choice of modeling algorithm was the greatest source of uncertainty in SDM performance and prediction maps, with some additional variation in performance associated with the comprehensiveness of the species presences used for modeling. Other sources of uncertainty that have received attention in the SDM literature such as variable collinearity and model domain contributed little to differences in SDM performance or predictions in this study. Predictions from different algorithms tended to be more variable at northern range margins for species with more northern distributions, which may complicate conservation planning at the leading edge of species' geographic ranges. The clear message emerging from this work is that researchers should use multiple algorithms for modeling rather than relying on predictions from a single algorithm, invest resources in compiling a comprehensive set of species presences, and explicitly evaluate uncertainty in SDM predictions at leading range margins.

Ecological Modelling↗
USGS2011

Compensatory effects of recruitment and survival when amphibian populations are perturbed by disease

The need to increase our understanding of factors that regulate animal population dynamics has been catalysed by recent, observed declines in wildlife populations worldwide. Reliable estimates of demographic parameters are critical for addressing basic and applied ecological questions and understanding the response of parameters to perturbations (e.g. disease, habitat loss, climate change). However, to fully assess the impact of perturbation on population dynamics, all parameters contributing to the response of the target population must be estimated. We applied the reverse‐time model of Pradel in Program mark to 6 years of capture–recapture data from two populations of Anaxyrus boreas (boreal toad) populations, one with disease and one without. We then assessed a priori hypotheses about differences in survival and recruitment relative to local environmental conditions and the presence of disease. We further explored the relative contribution of survival probability and recruitment rate to population growth and investigated how shifts in these parameters can alter population dynamics when a population is perturbed. High recruitment rates (0·41) are probably compensating for low survival probability (range 0·51–0·54) in the population challenged by an emerging pathogen, resulting in a relatively slow rate of decline. In contrast, the population with no evidence of disease had high survival probability (range 0·75–0·78) but lower recruitment rates (0·25). Synthesis and applications. We suggest that the relationship between survival and recruitment may be compensatory, providing evidence that populations challenged with disease are not necessarily doomed to extinction. A better understanding of these interactions may help to explain, and be used to predict, population regulation and persistence for wildlife threatened with disease. Further, reliable estimates of population parameters such as recruitment and survival can guide the formulation and implementation of conservation actions such as repatriations or habitat management aimed to improve recruitment.

Journal of Applied Ecology↗
USGS2009

Climate alters response of an endemic island plant to removal of invasive herbivores

Islands experience higher rates of species extinction than mainland ecosystems, with biological invasions among the leading causes; they also serve as important model systems for testing ideas in basic and applied ecology. Invasive removal programs on islands are conservation efforts that can also be viewed as powerful manipulative experiments, but few data are available to evaluate their effects. We collected demographic and herbivore damage data for Castilleja mollis Pennell, an endangered plant endemic to Santa Rosa Island, California, over a 12-year period before, during, and after the implementation of control for introduced cattle, deer, and elk. We used these long-term data to explore mechanisms underlying herbivore effects, assess the results of herbivore reduction at the scales of both individual plants and populations, and determine how temporal variability in herbivory and plant demography influenced responses to herbivore removals. For individual plants, herbivore effects mediated by disturbance were greater than those of grazing. Deer and elk scraping of the ground substantially increased plant mortality and dormancy and reduced flowering and growth. Stem damage from browsing did not affect survivorship but significantly reduced plant growth and flower production. Herbivore control successfully lowered damage rates, which declined steeply between 1997 and 2000 and have remained relatively low. Castilleja mollis abundances rose sharply after 1997, suggesting a positive effect of herbivore control, but then began to decline steadily again after 2003. The recent decline appears to be driven by higher mean growing season temperatures; interestingly, not only reductions in scraping damage but a period of cooler conditions were significant in explaining increases in C. mollis populations between 1997 and 2002. Our results demonstrate strong effects of introduced herbivores on both plant demography and population dynamics and show that climate-driven variation may counteract and mask positive responses to herbivore removal. Regional mean temperatures already have risen significantly over the last 50 years, suggesting that climate change could increasingly swamp the effects of management targeted at other environmental problems. Similar interactions between climate and invasive species will play an even greater role in future management, with long-term data sets like this critical to quantifying such effects. ?? 2009 by the Ecological Society of America.

Ecological Applications↗
USGS2012

Matrix population models from 20 studies of perennial plant populations

Demographic transition matrices are one of the most commonly applied population models for both basic and applied ecological research. The relatively simple framework of these models and simple, easily interpretable summary statistics they produce have prompted the wide use of these models across an exceptionally broad range of taxa. Here, we provide annual transition matrices and observed stage structures/population sizes for 20 perennial plant species which have been the focal species for long-term demographic monitoring. These data were assembled as part of the "Testing Matrix Models" working group through the National Center for Ecological Analysis and Synthesis (NCEAS). In sum, these data represent 82 populations with >460 total population-years of data. It is our hope that making these data available will help promote and improve our ability to monitor and understand plant population dynamics.

Ecology↗
USGS2018

Toward salt marsh harvest mouse recovery: A review

The salt marsh harvest mouse (SMHM, Reithrodontomys raviventris ) is an endangered species, endemic to the San Francisco Estuary. Despite being protected for almost half a century and being included in a large number of recovery, restoration, and management plans, significant data gaps hinder conservation and management of the species, a challenge further complicated by developing threats such as climate change. In this review, we present the current state of knowledge; highlight research gaps on habitat requirements and distribution, taxonomic status and genetic structure, physiology, reproduction and demographics, population dynamics, and behavior and community interactions; and present an overview of threats to the species. Our review indicates that substantial data gaps exist; although some aspects of SMHM ecology, such as habitat use, have been addressed extensively, others, such as the effects of environmental contamination, are largely unaddressed. We suggest that conservation and restoration-planning processes consider experimental approaches within restoration designs to address these deficiencies. Continued investment in basic and applied SMHM ecology to collect baseline and long-term data will also be beneficial. Additionally, further coordination among managers and researchers can facilitate more effective responses to uncertainties and emerging threats, especially climate change, which threatens the SMHM and its habitat throughout its range.

San Francisco Estuary and Watershed Science↗
USGS2010

BRIDGES: Evolution of basic and applied linkages in benthic science

Growing awareness of environmental degradation resulted in stricter environmental regulations and laws for aquatic ecosystems. These regulations were followed by an increase in applied research and monitoring beginning in the early 1970s. The number of applied scientists who were members of the North American Benthological Society grew at a commensurate rate. The editors of J-NABS recognized that, despite these increases, submitted manuscripts mostly addressed basic science. In response, the BRIDGES section of J-NABS was created in 1994 to provide a forum for linking basic ecological principles to applied science problems and issues. We examined the emergence of applied science topics in J-NABS and its predecessor, Freshwater Invertebrate Biology , from their beginning in 1982 to 2009. We classified papers among 11 categories that included a basic/applied science linkage. In the 1980s, applied papers were predominantly on effects of eutrophication/pollution and landuse changes. When BRIDGES was established in 1994, papers were solicited by editors and BRIDGES sections usually included >1 paper on a common theme to express complementary or alternate viewpoints. Forty-two papers appeared in BRIDGES between 1994 and 2009, but the number per issue declined after 2001. The total number of applied science papers in J-NABS has increased since ∼1994. Citation analysis of BRIDGES papers illustrates how information is being cited, but applied papers often are used in ways that might not lead to citations. BRIDGES transitioned to a new format in September 2009 to address new types of complex, multifaceted linkages. All new BRIDGES articles will be open access, and authors will be encouraged to produce lay-language fact sheets and to post them on the web.

Journal of the North American Benthological Societ↗
USGS2010

Assessing macroinvertebrate biodiversity in freshwater ecosystems: Advances and challenges in dna-based approaches

Assessing the biodiversity of macroinvertebrate fauna in freshwater ecosystems is an essential component of both basic ecological inquiry and applied ecological assessments. Aspects of taxonomic diversity and composition in freshwater communities are widely used to quantify water quality and measure the efficacy of remediation and restoration efforts. The accuracy and precision of biodiversity assessments based on standard morphological identifications are often limited by taxonomic resolution and sample size. Morphologically based identifications are laborious and costly, significantly constraining the sample sizes that can be processed. We suggest that the development of an assay platform based on DNA signatures will increase the precision and ease of quantifying biodiversity in freshwater ecosystems. Advances in this area will be particularly relevant for benthic and planktonic invertebrates, which are often monitored by regulatory agencies. Adopting a genetic assessment platform will alleviate some of the current limitations to biodiversity assessment strategies. We discuss the benefits and challenges associated with DNA-based assessments and the methods that are currently available. As recent advances in microarray and next-generation sequencing technologies will facilitate a transition to DNA-based assessment approaches, future research efforts should focus on methods for data collection, assay platform development, establishing linkages between DNA signatures and well-resolved taxonomies, and bioinformatics. ?? 2010 by The University of Chicago Press.

The Quarterly Review of Biology↗
USGS2009

Identifying across‐system sources of variation in a generalist freshwater fish: Correlates of total and size‐specific abundance of yellow perch

Variation in fish abundance across systems presents a challenge to our understanding of fish populations because it limits our ability to predict and transfer basic ecological principles to applied problems. Yellow perch ( Perca flavescens ) is an ideal species for exploring environmental and biotic correlates across system because it is widely distributed and physiologically tolerant. In 16 small, adjacent systems that span a wide range of environmental and biotic conditions, yellow perch were sampled with a standard suite of gear. Water quality, morphometry, vegetation, invertebrates and fish communities were concurrently measured. Multimodel inference was used to prioritise regressors for the entire yellow perch sample and three size groups (35-80, 81-180, ≥181 mm TL). Across systems, pH and fish richness were identified as the key drivers of yellow perch abundance. At very low pH (<4.0), few fish species and few yellow perch individuals were found. At ponds with moderately low pH (4.0–4.8), numbers of yellow perch increased. Ponds with high pH (>4.8) had many other species and few yellow perch. Similar patterns for pH and fish community were observed for the two largest‐size classes. Negative interactions were observed between the medium‐ and large‐sized yellow perch and between the largest and smallest yellow perch, although interspecific interactions were weaker than expected. This examination of variability for an indicator species and its component‐size classes provides ecological understanding that can help frame the larger‐scale sampling programs needed for the conservation of freshwater fish.

Ecology of Freshwater Fish↗
USGS2010

Ecological hierarchies and self-organisation - Pattern analysis, modelling and process integration across scales

A continuing discussion in applied and theoretical ecology focuses on the relationship of different organisational levels and on how ecological systems interact across scales. We address principal approaches to cope with complex across-level issues in ecology by applying elements of hierarchy theory and the theory of complex adaptive systems. A top-down approach, often characterised by the use of statistical techniques, can be applied to analyse large-scale dynamics and identify constraints exerted on lower levels. Current developments are illustrated with examples from the analysis of within-community spatial patterns and large-scale vegetation patterns. A bottom-up approach allows one to elucidate how interactions of individuals shape dynamics at higher levels in a self-organisation process; e.g., population development and community composition. This may be facilitated by various modelling tools, which provide the distinction between focal levels and resulting properties. For instance, resilience in grassland communities has been analysed with a cellular automaton approach, and the driving forces in rodent population oscillations have been identified with an agent-based model. Both modelling tools illustrate the principles of analysing higher level processes by representing the interactions of basic components.The focus of most ecological investigations on either top-down or bottom-up approaches may not be appropriate, if strong cross-scale relationships predominate. Here, we propose an 'across-scale-approach', closely interweaving the inherent potentials of both approaches. This combination of analytical and synthesising approaches will enable ecologists to establish a more coherent access to cross-level interactions in ecological systems. ?? 2010 Gesellschaft f??r ??kologie.

Basic and Applied Ecology↗
USGS2020

Testing prediction accuracy in short-term ecological studies

Applied ecology is based on an assumption that a management action will result in a predicted outcome. Testing the prediction accuracy of ecological models is the most powerful way of evaluating the knowledge implicit in this cause-effect relationship, however, the prevalence of predictive modeling and prediction testing are spreading slowly in ecology. The challenge of prediction testing is particularly acute for small-scale studies, because withholding data for prediction testing (e.g., via k -fold cross validation) can reduce model precision. However, by necessity small-scale studies are common. We use one such study that explored small mammal abundance along an elevational gradient to test prediction accuracy of models with varying degrees of information content. For each of three small mammal species, we conducted 5000 iterations of the following process: (1) randomly selected 75 % of the data to develop generalized linear models of species abundance that used detailed site measurements as covariates, (2) used an information theoretic approach to compare the top model with detailed covariates to habitat type-only and null models constructed with the same data, (3) tested those models’ ability to predict the 25 % of the randomly withheld data, and (4) evaluated prediction accuracy with a quadratic loss function. Detailed models fit the model-evaluation data best but had greater expected prediction error when predicting out-of-sample data relative to the habitat type models. Relationships between species and detailed site variables may be evident only within the framework of explicitly hierarchical analyses. We show that even with a small but relatively typical dataset ( n = 28 sampling locations across 125 km over two years), researchers can effectively compare models with different information content and measure models’ predictive power, thus evaluating their own ecological understanding and defining the limits of their inferences. Identifying the appropriate scope of inference through prediction testing is ecologically valuable and is attainable even with small datasets.

Maine, New Hampshire↗
USGS2007

The diversity-biomass-productivity relationships in grassland management and restoration

Diversity, biomass, and productivity, the three key community/ecosystem variables, are interrelated and pose reciprocal influences on each other. The relationships among the three variables have been a central focus in ecology and formed two schools of fundamentally different nature with two related applications: (1) management - how biomass manipulation (e.g., grazing, burning) affects diversity and productivity, and (2) restoration - how diversity manipulation (e.g., seeding, planting) affects biomass and productivity. In the past, the two apparently related aspects have been studied intensively but separately in basic research and the reciprocal effects of the three variables and applied aspects have not been jointly addressed. In most cases, optimal management often involves regulating biomass so that high diversity and productivity or other preferred habitat characteristics can be achieved and maintained, while restoration usually involves planting/seeding a certain number and/or combination of native species so that the native structure and function of the habitat can be restored and degraded ecosystems can recover faster. This article attempts to unify these two schools and discusses the significance and implications of the diversity-biomass-productivity relationships in practice, with particular emphasis on grassland ecosystems. ?? 2006 Gesellschaft fu??r O??kologie.

Basic and Applied Ecology↗
USGS2003

Demographic stochasticity in small remnant populations of the declining distylous plant Primula veris

We studied ecological consequences of distyly for the declining perennial plant Primula veris in the Swiss Jura. Distyly favours cross-fertilization and avoids inbreeding, but may lead to pollen limitation and reduced reproduction if morph frequencies deviate from 50 %. Disassortative mating is promoted by the reciprocal position of stigmas and anthers in the two morphs (pin and thrum) and by intramorph incompatibility and should result in equal frequencies of morphs at equilibrium. However, deviations could arise because of demographic stochasticity, the lower intra-morph incompatibility of the pin morph, and niche differentiation between morphs. Demographic stochasticity should result in symmetric deviations from an even morph frequency among populations and in increased deviations with decreasing population size. If crosses between pins occurred, these would only generate pins, and this could result in a pin-bias of morph frequencies in general and in small populations in particular. If the morphs have different niches, morph frequencies should be related to environmental factors, morphs might be spatially segregated, and morphological differences between morphs would be expected. We tested these hypotheses in the declining distylous P. veris. We studied morph frequencies in relation to environmental conditions and population size, spatial segregation in field populations, morphological differences between morphs, and growth responses to nutrient addition. Morph frequencies in 76 populations with 1 - 80000 flowering plants fluctuated symmetrically about 50 %. Deviations from 50 % were much larger in small populations, and sixof the smallest populations had lost one morph altogether. In contrast, morph frequencies were neither related to population size nor to 17 measures of environmental conditions. We found no spatial segregation or morphological differences in the field or in the common garden. The results suggest that demographic stochasticity caused deviations of the morph ratiofrom unity in small populations. Demographic stochasticity was probably caused by the random elimination of plants during the fragmentation of formerly large continuous populations. Biased morph frequencies may be one of the reasons for the strongly reduced reproduction in small populations of P. veris.

Basic and Applied Ecology↗